Effects of Occupational Stress Management Intervention Programs: A Meta-Analysis

Abstract

A meta-analysis was conducted to determine the effectiveness of stress management interventions in occupational settings. Thirty-six experimental studies were included, representing 55 interventions. Total sample size was 2,847. Of the participants, 59% were female, mean age was 35.4, and average length of intervention was 7.4 weeks. The overall weighted effect size (Cohen's d) for all studies was 0.526 (95% confidence interval = 0.364, 0.687), a significant medium to large effect. Interventions were coded as cognitive-behavioral, relaxation, organizational, multimodal, or alternative. Analyses based on these subgroups suggested that intervention type played a moderating role. Cognitive-behavioral programs consistently produced larger effects than other types of interventions, but if additional treatment components were added the effect was reduced. Within the sample of studies, relaxation interventions were most frequently used, and organizational interventions continued to be scarce. Effects were based mainly on psychological outcome variables, as opposed to physiological or organizational measures. The examination of additional moderators such as treatment length, outcome variable, and occupation did not reveal significant variations in effect size by intervention type.

Full text

Effects of Occupational Stress Management Intervention Programs:
A Meta-Analysis
Katherine M. Richardson and Hannah R. Rothstein
Baruch College, City University of New York
A meta-analysis was conducted to determine the effectiveness of stress management interventions
in occupational settings. Thirty-six experimental studies were included, representing 55 interven-
tions. Total sample size was 2,847. Of the participants, 59% were female, mean age was 35.4, and
average length of intervention was 7.4 weeks. The overall weighted effect size (Cohen’s d) for all
studies was 0.526 (95% confidence interval ⫽ 0.364, 0.687), a significant medium to large effect.
Interventions were coded as cognitive– behavioral, relaxation, organizational, multimodal, or
alternative. Analyses based on these subgroups suggested that intervention type played a mod-
erating role. Cognitive–behavioral programs consistently produced larger effects than other types
of interventions, but if additional treatment components were added the effect was reduced.
Within the sample of studies, relaxation interventions were most frequently used, and organiza-
tional interventions continued to be scarce. Effects were based mainly on psychological outcome
variables, as opposed to physiological or organizational measures. The examination of additional
moderators such as treatment length, outcome variable, and occupation did not reveal significant
variations in effect size by intervention type.
Keywords: stress management, meta-analysis, employee intervention
Employee stress has increasingly become a con-
cern for many organizations. To paraphrase the “fa-
ther of stress,” Hans Selye, stress is an unavoidable
consequence of life, and therefore an unavoidable
consequence of organizations. Americans are work-
ing longer and harder, and job stress continues to
increase. The average work year for prime-age work-
ing couples in the United States increased by nearly
700 hours in the past two decades (Murphy & Sauter,
2003; U.S. Department of Labor, 1999). From 1997
to 2001, the number of workers calling in sick be-
cause of stress tripled. The American Institute of
Stress reported that stress is a major factor in up to
80% of all work-related injuries and 40% of work-
place turnovers (Atkinson, 2004). This is not solely
an American phenomenon. The Confederation of
British Industry reported stress as the second highest
cause of absenteeism among nonmanual workers in
the United Kingdom, and the European Foundation
for the Improvement of Living and Working Condi-
tions reported that stress affects a third of the Euro-
pean working population (Giga, Cooper, & Faragher,
2003). In Australia, most states report an increasing
number of annual workers’ compensation claims
resulting from workplace stress (Caulfield, Chang,
Dollard, & Elshaug, 2004). Organizations provide a
major portion of the total stress experienced by a
person as a result of the amount of time spent on the
job, the demands for performance, and the interaction
with others in the workplace (DeFrank & Cooper,
1987).
Although it is not possible to eliminate stress en-
tirely, people can learn to manage it. Many organi-
zations have adopted stress management training pro-
grams to try and reduce the stress levels of their
workforce. A stress management intervention (SMI)
is any activity or program initiated by an organization
that focuses on reducing the presence of work-related
stressors or on assisting individuals to minimize the
negative outcomes of exposure to these stressors
(Ivancevich, Matteson, Freedman, & Phillips, 1990).
Interest in strategies to reduce stress at work has
increased steadily since the 1970s. According to the
U.S. Department of Health and Human Services,
national surveys conducted in 1985, 1992, and 1999
found the prevalence of stress management and coun-
seling programs among private-sector worksites in
those years was 27%, 37%, and 48%, respectively
(Nigam, Murphy, & Swanson, 2003). The popularity
Katherine M. Richardson and Hannah R. Rothstein, De-
partment of Management, Zicklin School of Business, Ba-
ruch College, City University of New York.
Correspondence concerning this article should be addressed
to Katherine M. Richardson, Baruch College, City University
of New York, One Bernard Baruch Way, New York, NY
10010. E-mail: katherine_mcpadden@baruch.cuny.edu
Journal of Occupational Health Psychology
2008, Vol. 13, No. 1, 69 –93
Copyright 2008 by the American Psychological Association
1076-8998/08/$12.00 DOI: 10.1037/1076-8998.13.1.69
69

of worksite stress management programs has grown
significantly abroad as well as in the United States.
Job Stress and Interventions
Newman and Beehr (1979, p.1) defined job stress
as “a situation wherein job-related factors interact
with the worker to change his or her psychological
and/or physiological condition such that the person is
forced to deviate from normal functioning.” Implicit
in this definition is the belief that work-related factors
are a cause of stress and that the individual outcomes
may be psychological, physiological, or some com-
bination of these. A SMI may attempt to change these
work-related factors, assist employees in minimizing
the negative effects of these stressors, or both.
Ivancevich et al. (1990) developed a conceptual
framework for the design, implementation, and eval-
uation of SMIs. According to the model, interven-
tions can target three different points in the stress
cycle: (a) the intensity of stressors in the workplace,
(b) the employee’s appraisal of stressful situations, or
(c) the employee’s ability to cope with the outcomes.
The components of actual SMIs vary widely, encom-
passing a broad array of treatments that may focus on
the individual, the organization, or some combination
(DeFrank & Cooper, 1987; Giga, Noblet, Faragher,
& Cooper, 2003).
Interventions may be classified as primary, sec-
ondary, or tertiary. Primary interventions attempt to
alter the sources of stress at work (Murphy & Sauter,
2003). Examples of primary prevention programs
include redesigning jobs to modify workplace stres-
sors (cf. Bond & Bunce, 2000), increasing workers’
decision-making authority (cf. Jackson, 1983), or
providing coworker support groups (cf. Carson et al.,
1999; Cecil & Forman, 1990; Kolbell, 1995). In
contrast, secondary interventions attempt to reduce
the severity of stress symptoms before they lead to
serious health problems (Murphy & Sauter, 2003).
Tertiary interventions—such as employee assistance
programs—are designed to treat the employee’s
health condition via free and confidential access to
qualified mental health professionals (Arthur, 2000).
The most common SMIs are secondary prevention
programs aimed at the individual and involve instruc-
tion in techniques to manage and cope with stress
(Giga, Cooper, & Faragher et al., 2003). Examples
are cognitive– behavioral skills training, meditation,
relaxation, deep breathing, exercise, journaling, time
management, and goal setting.
Cognitive– behavioral interventions are designed
to educate employees about the role of their thoughts
and emotions in managing stressful events and to
provide them with the skills to modify their thoughts
to facilitate adaptive coping (cf. Bond & Bunce,
2000). These interventions are intended to change
individuals’ appraisal of stressful situations and their
responses to them. For example, employees are
taught to become aware of negative thoughts or irra-
tional beliefs and to substitute positive or rational
ideas (Bellarosa & Chen, 1997).
Meditation, relaxation, and deep-breathing inter-
ventions are designed to enable employees to reduce
adverse reactions to stresses by bringing about a
physical and/or mental state that is the physiological
opposite of stress (cf. Benson, 1975). Typically, in
meditation interventions, the employee is taught to
focus on a single object or an idea and to keep all
other thoughts from his or her mind, although some
programs teach employees to observe everything that
goes through their mind without getting involved
with or attached to them. Meditation interventions
often also include relaxation therapy and deep breath-
ing exercises. Relaxation therapy focuses on the con-
scious and controlled release of muscle tension. Deep
breathing exercises focus on increasing the intake of
oxygen and the release of carbon dioxide, although
muscle and mental relaxation is often an additional
goal of slowing and deepening the breath.
Exercise programs generally focus on providing a
physical release from the tension that builds up in
stressful situations, increasing endorphin production,
or both, although some have the goal of focusing the
employee’s attention on physical activity (rather than
on the stressors) or providing an outlet for anger or
hostility (cf. Bruning & Frew, 1987).
Journaling interventions require the employee to
keep a journal, log, or diary of the stressful events in
his or her life (cf. Alford, Malouff, & Osland, 2005).
The journal is used as a means of assisting the em-
ployee to monitor stress levels, to identify the recur-
ring causes of stress, and to note his or her reactions.
Journals are also used to formulate action plans for
managing stress.
Time management and goal-setting interventions
are designed to help people manage their time better,
both on and off the job. Employees often operate
under time pressure and are required to work on
multiple tasks simultaneously. Working under such
conditions can be particularly stressful. Time man-
agement interventions provide skills training in the
areas of goal setting, scheduling and prioritizing
tasks, self-monitoring, problem solving, delegating,
negotiating, and conflict resolution (cf. Bruning &
Frew, 1987; N. C. Higgins, 1986).
70 RICHARDSON AND ROTHSTEIN

Electromyogram (EMG) biofeedback training pro-
vides participants with continuous feedback of mus-
cle tension levels (cf. Murphy, 1984b). The objective
is to consciously trigger the relaxation response and
control involuntary stress responses from the auto-
nomic nervous system. Through the use of electronic
feedback measuring forehead muscle tension or hand
temperature, patients receive feedback via audible
tones or visual graphs on a computer screen. During
the process they learn to monitor their physiological
arousal levels and physically relax their bodies, ac-
tually changing their heart rate, brain waves, muscle
contractions, and more.
SMIs may focus on any one particular strategy
outlined above, such as relaxation training (cf. Fiedler,
Vivona-Vaughan, & Gochfeld, 1989; R. K. Peters,
Benson, & Porter, 1977), or combine multiple com-
ponents to create a comprehensive training regimen
that may include any of the following: cognitive–
behavioral skills, meditation, assertiveness, social
support, and so forth (cf. Bruning & Frew, 1986,
1987; de Jong & Emmelkamp, 2000; Zolnierczyk-
Zreda, 2002). A trained instructor or counselor in
either small group or one-on-one sessions generally
teaches the methods, but techniques are sometimes
self-taught with the aid of books and tapes (cf.
Aderman & Tecklenberg, 1983; Murphy, 1984b;
Vaughn, Cheatwood, Sirles, & Brown, 1989) and
increasingly via computers (cf. Hoke, 2003;
Shimazu, Kawakami, Irimajiri, Sakamoto, & Amano,
2005). Treatment programs are usually administered
over several weeks and may take place at the work-
site or at an outside location. Depending on the
treatment method used, session length may vary from
15-min breaks to all-day seminars.
Which Interventions Are Most Effective?
The effectiveness of SMIs is measured in a variety
of ways. Researchers may assess outcomes at the
organizational level (e.g., absenteeism or productiv-
ity) or at the individual level, using psychological
(e.g., stress, anxiety, or depression) or physiological
(e.g., blood pressure or weight) measures. Given the
wide array of stress management programs and out-
come variables, there has been much debate in the
literature as to which interventions, if any, are most
effective (Briner & Reynolds, 1999; Bunce &
Stephenson, 2000; Caulfield et al., 2004; DeFrank &
Cooper, 1987; Giga, Noblet, Faragher, & Cooper, 2003;
Ivancevich et al., 1990; Mimura & Griffiths, 2002;
Murphy, 1984a; Newman & Beehr, 1979; Nicholson,
Duncan, Hawkins, Belcastro, & Gold, 1988; van der
Hek & Plomp, 1997). Some critics have claimed that
studies in this area are inconclusive and based largely
on anecdotes, testimonials, and methodologically weak
research (Briner & Reynolds, 1999; Ivancevich et al.,
1990).
Newman and Beehr (1979) were among the first
researchers to perform a comprehensive narrative
review of personal and organizational strategies for
handling job stress, examining both medical and psy-
chological literature. They reported a significant lack
of empirical research in the domain and challenged
industrial/organizational psychologists to bring their
experience to the field of job stress– employee health
(Newman & Beehr, 1979). During the 1980s, several
researchers reviewed the SMI literature (DeFrank &
Cooper, 1987; Murphy, 1984a; Nicholson et al.,
1988). Murphy (1984a) performed a narrative review
of 13 studies and concluded that they generally dem-
onstrated acceptable positive effects, but noted that
the “reports varied significantly in terms of the ade-
quacy of the methodology used” (p. 2). DeFrank and
Cooper (1987) criticized the methodological quality
of the studies reviewed by Murphy. Three of the 13
studies from that review did not use control groups,
and the majority had small sample sizes with low
power and short follow-up time frames, making it
difficult to assess the maintenance of gains.
Nicholson et al. (1988) expanded on Murphy’s
(1984a) work and identified 62 published evaluations
of stress management programs from the medicine,
public health, psychology, and education fields.
These included case studies, preexperiments, quasi-
experiments, and experimental studies (Nicholson et
al., 1988). Of the 62 studies examined, only 18 pro-
vided adequate data to quantitatively summarize the
results. Within these 18 studies, the average improve-
ment in the treatment groups was equal to three
quarters of one standard deviation in the control
group scores, yielding “mildly encouraging results”
(Nicholson et al., 1988). This translates into a Cohen’s
d of 0.75, which approaches a large effect (J. Cohen,
1988). However, only a third of the studies in Nicholson
et al.’s review included participants from occupational
settings. The remainder consisted of participants from a
variety of groups, including schoolchildren, juvenile
delinquents, college students, epilepsy patients, hyper-
tension patients, and substance abusers.
Over the past two decades, intervention studies in
occupational settings have proliferated, and research-
ers have conducted more focused reviews to examine
their effectiveness (Briner & Reynolds, 1999; Bunce
& Stephenson, 2000; Caulfield et al., 2004; Giga, No-
blet, Faragher, & Cooper, 2003; Mimura & Griffiths,
71EFFECTS OF STRESS MANAGEMENT INTERVENTIONS

2002; van der Hek & Plomp, 1997). Results have
continued to be mixed. Briner and Reynolds con-
ducted a narrative review of organization-level inter-
ventions (e.g., job redesign) and concluded that they
often have little or no effect. Bunce and
Stephenson examined interventions that focused on
individual-level outcomes and reviewed 27 studies,
assessing their levels of descriptive information and
statistical power. They reported that “at present the
quality of reporting and research design is such that it
is difficult to form an impression of what type of SMI
is appropriate to whom, and in what circumstances”
(p. 198).
More recent narrative reviews have focused on
particular job occupations, such as the nursing pro-
fession (Mimura & Griffiths, 2002) or mental health
professionals (Edwards, Hannigan, Fothergill, &
Burnard, 2002), or specific geographic regions,
such as the United Kingdom (Giga, Noblet, Faragher,
& Cooper, 2003) and Australia (Caulfield et al.,
2004). A problem with such focused reviews, how-
ever, is that they result in a small number of studies,
and each study may compare multiple intervention
methods or outcomes. This makes it difficult to ob-
tain precise estimates of the relative effectiveness of
different interventions, or to assess generalizability of
results.
The accumulation of stress management studies
across a wide variety of occupational and geographic
settings, assessing a multitude of intervention tactics,
calls for a systematic review. In behavioral and med-
ical research, as well as in other fields, meta-analysis
has become the widely accepted technique for assess-
ing the effectiveness of interventions. It has replaced
the traditional narrative assessment of a body of
research as a better way to accumulate data and
synthesize them into generalizable knowledge (Eden,
2002). The primary goals of meta-analysis are to
derive the best estimate of the population effect size
and to determine whether there are any sources of
variance around this effect (Rothstein, McDaniel, &
Borenstein, 2002).
A study by van der Klink, Blonk, Schene, and van
Dijk (2001) used meta-analytic techniques to exam-
ine the effectiveness of worksite stress interventions.
The researchers meta-analyzed data from 48 inter-
ventions published in 45 articles between 1977 and
1996. A small but significant overall effect size was
found (d ⫽ 0.34). When effects were broken down by
intervention type, cognitive– behavioral interventions
achieved the largest effect size (d ⫽ 0.68), followed
by multimodal (d ⫽ 0.51), relaxation (d ⫽ 0.35), and
organization-focused programs (d ⫽ 0.08). The
present study seeks to update the van der Klink et al.
meta-analysis. We believe that a new meta-analysis is
appropriate for three reasons. First, although the
van der Klink et al. review was published in 2001, it
includes studies published only through 1996, and a
considerable number of new, methodologically rig-
orous studies have been conducted since that time.
There is a growing consensus that meta-analyses and
systematic reviews, particularly those with health
policy or practice implications, should be updated
whenever a sizable number of new studies appear (cf.
Chalmers & Haynes, 1994; Clark, Donovan, &
Schoettker, 2006; J. P. T. Higgins & Green, 2005).
This review expands the eligibility timeframe
through early 2006.
Second, van der Klink et al. (2001) included stud-
ies of varying study designs and methodological
quality. Nine of their included studies used quasi-
experimental designs, and others did not include a
no-treatment control or comparison group. In addi-
tion, the van der Klink et al. meta-analysis included
seven randomized experiments that did not report
sufficient statistics to calculate an effect size or that
reported results of significant outcomes and not oth-
ers. They did this by making assumptions about the
probability values in these studies. As one of the
consistent criticisms of studies of SMIs is that they
are methodologically weak, our goal was to focus
only on studies with methodologically strong de-
signs. We therefore included only those interventions
that were evaluated using a true experimental design,
with random assignment of participants to treatment
and control groups. This reduces the threat of selec-
tion bias and increases the internal validity of the
included studies (Cook & Campbell, 1976) and,
therefore, the validity of the meta-analytic results.
Finally, the van der Klink et al. (2001) review was
based entirely on published journal articles and ex-
cluded dissertations, conference proceedings, book
chapters, and the like. This exclusion of so-called
“gray literature” has been shown to increase the
threat that publication bias (a tendency toward prep-
aration, submission, and publication of research find-
ings that is based on the nature and direction of the
research results rather than on the quality of the
research; Dickersin, 2005) will affect the meta-
analytic results. Publication bias affects the degree to
which published literature is representative of all the
available scientific evidence; when the research that
is readily available differs in its results from the
results of all the research that has been done in an
area, we are in danger of drawing the wrong conclu-
sion about that body of research (Rothstein, Sutton,
72 RICHARDSON AND ROTHSTEIN

& Borenstein, 2005). In order to minimize the threat
of publication bias, the current meta-analysis in-
cluded experimental studies from both published and
unpublished sources.
Our meta-analysis had two main goals. First, it was
intended to bring together and synthesize experimen-
tal studies of SMIs that have been conducted (and
reported) in a variety of disciplines (e.g., education,
health care, organizational studies, and psychology)
to identify what works, how well it works, and where
or for whom it works. Second, we hoped to use our
meta-analytic results to identify areas in the stress
management literature where additional primary
studies are needed.
To summarize, we intended our systematic review
to improve on the van der Klink et al. (2001) meta-
analysis by drawing from an additional decade of
studies, by including only randomized experiments
with sufficient statistical data to compute effect sizes
without making additional assumptions about proba-
bility values, and by incorporating a more compre-
hensive literature search strategy. Rather than ex-
clude the seven randomized experiments from the
van der Klink et al. study for which they inferred p
values, we performed a sensitivity analysis using the
effect sizes for these studies that were imputed by
van der Klink et al. to determine whether their inclu-
sion changes our results. Our goals are to synthesize
research from a variety of disciplines to assess what
has been learned and also to identify areas in which
additional primary studies are needed.
Method
Literature Search
Studies that assessed the effectiveness of a work-
site SMI were collected from a variety of sources.
Because our intent was to build on the van der Klink
et al. (2001) meta-analysis, we began by obtaining all
45 studies used in that review. Second, we conducted
an electronic search of six databases: Academic
Search Premier, British Library Direct, Dissertations
Abstracts, ERIC, ProQuest ABI Inform Global, and
PsycARTICLES. These databases were chosen to
obtain studies from different countries in a broad
range of research fields, including social sciences,
health care, and education. In addition, several of
these databases include both published and unpub-
lished studies. For the Academic Search Premier,
British Library Direct, ERIC, and PsycARTICLES
databases, we entered the following search terms on
three lines: employee or work or management, AND
stress or wellness, AND program* or intervention or
prevention. This same procedure was followed for
the Dissertations Abstract database, but it yielded no
results. We therefore changed the search criteria to
two lines: worksite and stress and management, AND
program or intervention or prevention. For the Pro-
Quest ABI Inform Global database, the same search
terms were used but were entered on one line with
classification codes, as follows: SU(employee or
work or management) AND ((stress or wellness) w/2
(program* or intervention or prevention)) AND
CC(9130 or 5400). The classification codes 9130 and
5400 indicate experimental and theoretical work,
respectively. These electronic searches yielded
942 documents (Academic Search Premier ⫽ 377,
British Library Direct ⫽ 255, ERIC ⫽ 122,
PsycARTICLES ⫽ 99, Dissertation Abstracts ⫽
31, and Proquest ABI Inform Global ⫽ 58).
Third, we performed a network search and e-
mailed colleagues knowledgeable in the field to see if
they recommended any studies. We also attended the
American Psychological Association/National Insti-
tute for Occupational Safety and Health Work,
Stress, and Health 2006 conference and reviewed the
conference proceedings. Fourth, we performed a
snowball search and reviewed the reference list of
each article obtained to identify additional citations
beyond the electronic search. Finally, we searched
private and government-sponsored Web sites devoted
to stress research to locate additional unpublished
literature, including those for the American Institute
for Stress (www.stress.org), the Canadian Institute
of Stress (www.stresscanada.org), and the National
Institute for Occupational Health and Safety
(www.cdc.gov/niosh).
Criteria for Inclusion
A study had to meet the following criteria to be
included in the meta-analysis: (a) be an experimental
evaluation of a primary or secondary SMI (i.e., em-
ployee assistance programs were excluded); (b) in-
clude participants from the working population (i.e.,
studies involving students were excluded) who are
not already diagnosed as having a major psychiatric
disorder (e.g., depression or posttraumatic stress) or
stress-related somatic disorder (e.g., hypertension);
(c) use random assignment to treatment and control
conditions; (d) report sample sizes, means, and stan-
dard deviations for both treatment and a no-treatment
or waiting-list control group; if means and standard
deviations were not reported, some other type of
statistic that could be converted into a standardized
73EFFECTS OF STRESS MANAGEMENT INTERVENTIONS

mean effect size (Cohen’s d) was necessary; and (e)
be written in English after 1976. This date was cho-
sen because it is the year the APA Task Force on
Health Research published a report that exhorted
psychologists, including industrial/organizational
psychologists, to take a role in examining the health
problems of Americans (Beehr & Newman, 1978).
Among the 45 articles used in the van der Klink et
al. (2001) meta-analysis, 19 met the inclusion criteria
outlined above and were included in our study. The
remaining 26 articles were excluded for the following
reasons: Nine used a quasi-experimental design with-
out random assignment, 8 did not include a no-
treatment comparison group, 7 did not report suffi-
cient statistics to calculate an effect size, 1 used a
student sample, and 1 did not include outcome vari-
ables related to stress or strain. We reviewed the
abstracts of the 942 articles identified in the elec-
tronic search online to determine whether to obtain
the studies for a full text review. Most studies were
excluded on initial abstract review because they
lacked a control group, did not include appropriate
participants (e.g., used students or patients with clin-
ically diagnosed disorders), assessed employee atti-
tudes about interventions rather than the behavioral
effects of the interventions, or had already been iden-
tified via the van der Klink et al. study. In total, 50
experimental studies were obtained for a full text
review. Of these, 37 were excluded because they
were quasi-experimental (17), did not use a control
group (9), used a student or patient sample (7), or did
not include the appropriate statistics (4). Thirteen
studies met all the inclusion criteria and were in-
cluded in the meta-analysis (9 peer-reviewed journal
articles and 4 unpublished dissertations). In addition,
19 from the van der Klink et al. meta-analysis were
included. During this process, we identified 19 other
nonempirical review articles and also obtained them
to examine the reference lists for additional studies.
The network search resulted in four usable studies
(one journal article, two book chapters, and one un-
published dissertation). The snowball search resulted
in 24 additional documents for review, and 2 of these
were used in the study. The searches on the stress
websites yielded no usable studies. In total, 38 arti-
cles were included in the current meta-analysis, rep-
resenting 36 separate studies and 55 interventions.
Coding Procedure
We coded the reports at five levels: study, treat-
ment– control contrast, sample, outcome, and effect
size. Study-level coding recorded the article’s full
citation, publication type, number of treatment–
control contrasts, and source of article (e.g., data-
base). The treatment–control contrast level was cre-
ated because several of the studies evaluated more
than one type of treatment. Although some of these
were totally independent evaluations, some had mul-
tiple treatment groups (each with nonoverlapping
participants) that were compared with a single con-
trol group. We considered each of these treatment–
control contrasts as a separate comparison for coding
purposes. At this level of coding, we recorded infor-
mation about the treatment and comparison groups,
including program components (e.g., cognitive–
behavioral skills training, meditation, exercise, etc.),
where the treatment and comparison groups worked,
where the program was delivered, who delivered the
treatment, and the duration of the program. We used
this information to code the intervention type as
primary, secondary, or a combination. At the sample
level, we coded the number of people in the sample
(before attrition), the types of workers, and demo-
graphic information including country of partici-
pants. At the outcome level, we recorded each de-
pendent variable and categorized them according to
psychological measures (e.g., general mental health,
anxiety, or depression), physiological measures (e.g.,
diastolic and systolic blood pressure or pulse), and
organizational measures (e.g., productivity or absen-
teeism). We also coded the type of measurement
scale (e.g., continuous) and the source of the data
(e.g., self-report). For each outcome variable, we then
coded the necessary information to calculate its effect
size, including treatment and comparison group sam-
ple sizes, the statistical data, the direction of the
effect size, and whether this difference was reported
as statistically significant by the original investigator.
We both coded the initial 10% of studies to assess
intercoder reliability. Because there was close to
100% agreement, Katherine M. Richardson coded the
remaining studies, reviewing unclear data when nec-
essary with Hannah R. Rothstein until a consensus
decision was reached.
Two of the studies that met our inclusion criteria
used groups as the unit of random assignment to
treatment or control conditions, rather than assigning
individuals. This clustering of individuals within
groups reduces the effective sample size of these
studies. As we have no basis for estimating this
effect, or for adjusting the weights of these two
studies, we used the original sample sizes in our
analyses. This should not have much of an impact on
the overall effect size estimates or on the moderator
analyses, but it will inflate the statistical significance
74 RICHARDSON AND ROTHSTEIN

levels of these two studies and underestimate the
confidence intervals (CIs) for them.
Statistical Procedures
Comprehensive Meta Analysis Version 2 software
(Borenstein, Hedges, Higgins, & Rothstein, 2005)
was used to conduct the statistical analyses. The
standardized mean difference (J. Cohen, 1992;
Lipsey & Wilson, 2001) was calculated to represent
the intervention effects reported in the eligible stud-
ies. This effect size statistic is defined as the differ-
ence between the treatment and control group means
on an outcome variable divided by their pooled stan-
dard deviations. For this meta-analysis, the random
effects model was most appropriate as heterogeneity
was expected owing to the variety of intervention
types and occupational settings. Our procedures were
analogous to a Hunter–Schmidt (1990) bare-bones
meta-analysis in that we made no corrections for
statistical artifacts other than sampling error. Our
decision was based on the lack of sufficient infor-
mation in the retrieved studies to appropriately
make such corrections (e.g., scale reliabilities). By
not adjusting for artifacts, it is expected that the
calculated mean effect sizes will underestimate
their actual values (Hunter & Schmidt, 1990). We
calculated effect sizes at the treatment– control
contrast level. Our meta-analysis represents the
combined effect of 55 independent interventions
within 36 studies. For studies that reported multi-
ple outcome variables, all applicable effect sizes
that could be extracted were calculated and coded.
However, we followed Lipsey and Wilson’s (2001)
advice that including multiple effect sizes from the
same intervention violates the assumption of inde-
pendent data points that is fundamental to most
common forms of statistical analysis and inflates
the sample size (N of effect sizes rather than N of
interventions). They recommended either using the
average of the outcomes at the treatment– control
contrast level to get a combined effect or selecting
the most representative outcome measure within
each module. Owing to the wide range of outcome
variables within our population of studies, we used
the average of the outcomes at the intervention
level for our overall analysis rather than introduce
subjectivity into the analysis process by selecting
what we felt would be most representative. We
also looked at individual outcomes in a series of
subgroup analyses. Each effect size was weighted
by its precision, so that interventions with larger
samples contributed more to the estimate of the
population effect size.
Results
Demographics
Table 1 summarizes the studies selected for the
meta-analysis. Thirty-eight articles were identified
that met the inclusion criteria, representing 36 sepa-
rate studies and 55 interventions. Total sample size
was 2,847 before attrition and 2,376 after attrition.
Individual sample sizes after attrition ranged from 14
to 219 participants, with a mean of 49 per interven-
tion. The participants represented a wide range of
occupations, including office workers, teachers,
nurses and hospital staff, factory workers, mainte-
nance personnel, and social services staff. Two thirds
of the studies were conducted in the United States,
and the remainder represented a diverse range of
countries, including Australia, Canada, China (Tai-
wan and Hong Kong), Israel, Japan, the Netherlands,
Poland, and the United Kingdom. Fifty-nine percent
of the participants were female (based on 28 studies)
and mean age was 35.4 (based on 18 studies). Aver-
age intervention length was 7.4 weeks. The mean
number of treatment sessions was 7.5, each lasting an
average of 1–2 hr.
Types of Interventions
The studies primarily assessed secondary interven-
tion strategies to reduce the severity of an employee’s
stress symptoms. Only 8 studies included compo-
nents that were considered primary intervention strat-
egies, such as increasing workers’ decision-making
authority (e.g., participatory action research) or social
support within the organization. All the intervention
studies compared at least one treatment group to a
no-treatment or waiting list control. Fourteen studies
evaluated two treatment groups versus the same com-
parison group, and 2 studies evaluated three treat-
ment groups versus the same control. Each treat-
ment– control contrast was treated as a separate
intervention for analysis purposes. The majority of
studies (k ⫽ 24) evaluated interventions conducted in
a group-training environment. Other modes of treat-
ment included individual counseling sessions (k ⫽
3); self-taught techniques using the Internet, tapes, or
books (k ⫽ 5); or a combination of varying methods
(k ⫽ 4). Twenty-five studies (69%) included relax-
ation and meditation techniques. Twenty studies
(56%) included cognitive– behavioral skills training.
75EFFECTS OF STRESS MANAGEMENT INTERVENTIONS

Table 1
Primary Studies Included in the Meta-Analysis
Author(s) and year
Treatment-control
contrast
Sample size
a
and
description
b
Treatment components Outcomes measured
c
Length
Intervention
type
Aderman & Tecklenberg
(1983)
A Various organizations
(T ⫽ 21, C ⫽ 15)
General stress education
seminar, plus meditation
and relaxation training via
audiotapes
Anxiety (Bendig, 1956) 12 weeks Relaxation
B Various organizations
(T ⫽ 19, C ⫽ 15)
General stress education
seminar
Alternative
Alford, Malouff, &
Osland (2005)
A Child protective services
officers, Australia
(T ⫽ 31, C ⫽ 30)
Journal writing about recent
stress reactions and
emotions
General mental health
(GHQ-12), positive
affect, negative
affect, job
satisfaction (JIG)
3 days Alternative
Bertoch, Nielson, Curley,
& Borg (1989)
A Teachers (T ⫽ 15, C ⫽
15)
Holistic program: deep
breathing, exercise,
relaxation, social support,
assertiveness, and
nutrition
Stress (DSP), stress
(OSI), stress (teacher
stress measure),
stress (structured
clinical interview)
12 weeks Multimodal
Bond & Bunce (2000) A Office workers (T ⫽ 24,
C ⫽ 20)
“Acceptance commitment
therapy”: cognitive-
behavioral skills to enhance
emotional coping
General mental health
(GHQ-12), depression
(Beck), motivation,
job satisfaction,
propensity to innovate
14 weeks Cognitive-
behavioral
B Office workers (T ⫽ 21,
C ⫽ 20)
“Innovation promotion”
program: goal setting,
participatory action, and
planning to enhance
problem-focused coping
Organizational
Bruning & Frew (1986,
1987)
A Officer workers (T ⫽ 16,
C ⫽ 16)
Management skills based on
cognitive-behavioral
techniques, goal setting,
time management,
communication, planning
Pulse, systolic &
diastolic blood
pressure, galvanics
kin response
8 weeks Multimodal
B Office workers (T ⫽ 15,
C ⫽ 16)
Relaxation and meditation
techniques
Relaxation
C Office workers (T ⫽ 15,
C ⫽ 16)
Exercise program Alternative
(table continues)
76 RICHARDSON AND ROTHSTEIN

Table 1
(continued)
Author(s) and year
Treatment-control
contrast
Sample size
a
and
description
b
Treatment components Outcomes measured
c
Length
Intervention
type
Carson et al. (1999) A Nurses, United Kingdom
(T ⫽ 27, C ⫽ 26)
Social support group to
enhance coping abilities
Stress (DCL), social
support (SOS), self-
esteem (RSES),
emotional exhaustion
(MBI), general
mental health (GHQ)
5 weeks Organizational
Cecil & Forman (1990) A Teachers (T ⫽ 16, C ⫽
19)
Stress inoculation training
(Meichenbaum, 1977)
School stress, task-
based stress, job
satisfaction, role
overload, social
support (all SISS),
coping skills
6 weeks Cognitive-
behavioral
B Teachers (T ⫽ 17, C ⫽
19)
Coworker support group Organizational
Chen (2006) A Office workers, Israel (T
⫽ 24 units, C ⫽ 13
units, N ⫽ 219
participants)
Active learning experience
designed to increase
participants’ personal
resources
Social support (House,
1981), perceived
control (Karasek,
1979)
1 week Alternative
Collins (2004) A Office workers (T ⫽ 9, C
⫽ 9)
Cognitive-behavioral skills,
communication, relaxation
techniques, time
management
Stress (JSI), burnout
(MBI), general
physical health,
anxiety (STAI)
5 weeks Multimodal
B Office workers (T ⫽ 8, C
⫽ 9)
Cognitive-behavioral skills,
relaxation techniques
Multimodal
de Jong & Emmelkamp
(2000)
A Various organizations,
the Netherlands (T ⫽
45, C ⫽ 41)
Muscle relaxation, cognitive-
behavioral skills, problem
solving, assertiveness
training (taught by clinical
psychologist)
Anxiety (Dutch STAI),
general mental health
(GHQ), general
physical health,
social support (SSI),
role overload (OSQ),
job dissatisfaction
(OSQ)
8 weeks Multimodal
B Various organizations,
the Netherlands (T ⫽
44, C ⫽ 41)
Muscle relaxation, cognitive-
behavioral skills, problem
solving, assertiveness
training (taught by trained
paraprofessionals)
Multimodal
(table continues)
77EFFECTS OF STRESS MANAGEMENT INTERVENTIONS

Table 1
(continued)
Author(s) and year
Treatment-control
contrast
Sample size
a
and
description
b
Treatment components Outcomes measured
c
Length
Intervention
type
Fava et al. (1991) A Army officers (T ⫽
20, C ⫽ 17)
Stress Type-A behavior
reduction program,
cognitive-behavioral
skills, relaxation, self-
esteem enhancement
Stress (global
assessment of recent
stress), stress (PSS),
general mental health
(Kellner’s Symptom
Q), exercise attitude
28 weeks Multimodal
Fiedler, Vivona-
Vaughan, & Gochfeld
(1989)
A Hazardous waste
workers (T ⫽ 31, C
⫽ 30)
Progressive muscle
relaxation, deep
breathing
Systolic blood pressure,
diastolic blood
pressure, general
severity index (SCL-
90)
9 weeks Relaxation
Ganster, Mayes, Sime, &
Tharp (1982)
A Office workers (T ⫽
36, C ⫽ 34)
Cognitive-behavioral
skills (Meichenbaum,
1975), progressive
muscle relaxation
Anxiety, depression,
irritation, general
physical health,
epinephrine,
norepinephrine
8 weeks Multimodal
Gildea (1988) A Foster care agency
workers (T ⫽ 9, C
⫽ 8)
Stress/anger
management training:
cognitive-behavioral
skills, journaling,
relaxation, education,
anger control
Systolic blood pressure,
diastolic blood
pressure, depression,
general physical
health, hostility, and
anxiety (all SCL-90)
n/a Multimodal
B Foster care agency
workers (T ⫽ 8, C
⫽ 8)
Relaxation, journaling Relaxation
N. C. Higgins (1986) A Office workers (T ⫽
17, C ⫽ 18)
Relaxation, systematic
desensitization
Emotional exhaustion
(MBI), strain (PSQ),
absenteeism
6 weeks Relaxation
B Office workers, mixed
(T ⫽ 18, C ⫽ 18)
Rational emotive therapy,
time management, goal
setting, assertiveness
training
Multimodal
Hoke (2003) A Various organizations
(T ⫽ 46, C ⫽ 53)
Twice weekly e-mails
that teach deep
breathing, exercise,
hypnosis, journaling,
meditation and
relaxation, imagery
Stress (PSS),
depression, anxiety,
anger, daily hassles
12 weeks Multimodal
(table continues)
78 RICHARDSON AND ROTHSTEIN

Table 1
(continued)
Author(s) and year
Treatment-control
contrast
Sample size
a
and
description
b
Treatment
components
Outcomes
measured
c
Length
Intervention
type
Jackson (1983) A Hospital workers (N
⫽ 66)
Introduction of staff
meetings to increase
staff participation
Role conflict, role
ambiguity, social
support, general
mental health
(GHQ), job
satisfaction,
absenteeism
24 weeks Organizational
Kolbell (1995) A Child protective
services workers (T
⫽ 13, C ⫽ 12)
Meditation and
relaxation training via
audiotapes
Emotional exhaustion
(MBI), general
physical health
(BSI), absenteeism
4 weeks Relaxation
B Child protective
services workers (T
⫽ 13, C ⫽ 12)
Social support group Organizational
Lee & Crockett (1994) A Hospital nurses,
Taiwan, China (T
⫽ 29, C ⫽ 28)
Assertiveness training
based on rational-
emotive therapy
(Ellis, 1962)
Assertiveness (RAS),
stress (PSS)
2 weeks Cognitive-
behavioral
Maddi, Kahn, & Maddi
(1998)
A Office workers, mid-
level managers (T
⫽ 18, C ⫽ 16)
“Hardiness training,”
based on cognitive-
behavioral techniques
Hardiness, job
satisfaction, strain,
general physical
health, social support
10 weeks Cognitive-
behavioral
B Office workers, mid-
level managers (T
⫽ 12, C ⫽ 16)
Relaxation and
meditation
Relaxation
Murphy (1984b) A Highway maintenance
workers (T ⫽ 15, C
⫽ 8)
Electromyographic
biofeedback
General physical health
and anxiety (BSI);
trait anxiety (STAI);
job dissatisfaction.
10 days Alternative
B Highway maintenance
workers (T ⫽ 11, C
⫽ 8)
Muscle relaxation via
cassette tapes
Relaxation
Peters, Benson, & Porter
(1977); Peters,
Benson, & Peters
(1977)
A Office workers, United
Kingdom (T ⫽ 54,
C ⫽ 36)
Daily 15-min breaks,
taught specific
relaxation technique
with deep breathing
General physical health
(Symptoms Index),
productivity, social
support, happiness,
systolic & diastolic
blood pressure
8 weeks Relaxation
B Office workers, United
Kingdom (T ⫽ 36,
C ⫽ 36)
Daily 15-min breaks, no
relaxation techniques
taught
Relaxation
(table continues)
79EFFECTS OF STRESS MANAGEMENT INTERVENTIONS

Table 1
(continued)
Author(s) and year
Treatment-control
contrast
Sample size
a
and
description
b
Treatment components Outcomes measured
c
Length
Intervention
type
Peters & Carlson (1999) A University maintenance
workers (T ⫽ 21, C
⫽ 19)
Health education,
cognitive-behavioral
skills, goal setting,
and relaxation
Anxiety, anger, and
depression (STPI),
health self-efficacy,
job satisfaction,
systolic/diastolic
blood pressure,
cholesterol
10 weeks Multimodal
Pruitt (1992) A Army personnel (T ⫽
31, C ⫽ 33)
Stress awareness
education,
assertiveness, time
management,
relaxation via
audiotapes
Anxiety (STAI),
anxiety (SCL-90),
systolic & diastolic
blood pressure
n/a Multimodal
Shapiro, Astin, Bishop,
& Cordova (2005)
A Health care
professionals (T ⫽
18, C ⫽ 10)
Mindfulness-based stress
reduction (meditation,
deep breathing, yoga)
Burnout, general
mental health (GSI),
perceived stress
8 weeks Relaxation
Sharp & Forman (1985) A Teachers (T ⫽ 30, C
⫽ 30)
Stress inoculation training
(Meichenbaum, 1977)
Anxiety (TQ4), anxiety
(STAI, state),
anxiety (STAI, trait)
4 weeks Cognitive-
behavioral
B Teachers (T ⫽ 30, C
⫽ 30)
Classroom management
skills training
Alternative
Shimazu, Kawakami,
Irimajiri, Sakamoto, &
Amano (2005)
A Office workers in a
construction
machinery
company, Japan (T
⫽ 100, C ⫽ 104)
Self-paced online
intervention teaching
cognitive-behavioral
and coping techniques
Self-efficacy, stress
(BJSQ), general
physical health, job
satisfaction
11 weeks Cognitive-
behavioral
Stanton (1991) A Administrative office
workers, Australia
(T ⫽ 15, C ⫽ 15)
“Ego-enhancement”
relaxation techniques
Stress (“stress
thermometer”)
n/a Relaxation
Thomason & Pond
(1995)
A Custodial staff (T ⫽
14, C ⫽ 13)
Cognitive-behavioral
skills, relaxation,
imagery, and self-
management skills
General mental health
(SCL-90), anxiety
(STAI), job
satisfaction (JIG),
blood pressure
6 weeks Multimodal
B Custodial staff (T ⫽
13, C ⫽ 13)
Cognitive-behavioral
skills, relaxation, and
imagery
Multimodal
C Custodial staff (T ⫽
14, C ⫽ 13)
Personal development
skills
Alternative
(table continues)
80 RICHARDSON AND ROTHSTEIN

Table 1
(continued)
Author(s) and year
Treatment-control
contrast
Sample size
a
and
description
b
Treatment components Outcomes measured
c
Length
Intervention
type
Tsai & Crockett (1993) A Hospital nurses,
Taiwan, China (T
⫽ 68, C ⫽ 69)
Relaxation training based
on cognitive-behavioral
model of relaxation
(Smith, 1990)
General mental health
(Chinese GHQ), stress
(Chinese NSC)
5 weeks Relaxation
Tunnecliffe, Leach, &
Tunnecliffe (1986)
A Teachers, Australia (T
⫽ 7, C ⫽ 7)
“Collaborative behavioral
consultation” focused on
problem-solving
approach
Teacher stress (TOSQ) 5 weeks Cognitive-
behavioral
B Teachers, Australia (T
⫽ 7, C ⫽ 7)
Relaxation training Relaxation
Vaughn, Cheatwood, Sirles,
& Brown (1989)
A Administrative
workers (T ⫽ 8, C
⫽ 10)
Progressive muscle
relaxation via audiotapes
Stress (SRI) 4 weeks Relaxation
von Baeyer & Krause (1983-
1984)
A Nurses in a burn
treatment unit,
Canada (T ⫽ 7, C
⫽ 7)
Cognitive-behavioral skills,
deep breathing,
relaxation, and role
playing
Anxiety (STAI, stait)
anxiety (STAI, trait)
1 week Multimodal
Wirth (1992) A Bakery employees (T
⫽ 28, C ⫽ 18)
Leader-facilitated SMI:
cognitive-behavioral
skills, emotional stress
management, relaxation,
health education
Locus of control, general
physical health (PSC),
absenteeism
4 weeks Multimodal
B Bakery employees (T
⫽ 15, C ⫽ 18)
Self-taught SMI: cognitive-
behavioral skills,
relaxation, health
education
Multimodal
Yung, Fung, Chan, & Lau
(2004)
A Administrative nursing
staff, Hong Kong,
China (T ⫽ 17, C
⫽ 30)
Relaxation using stretching
and releasing of muscles
Anxiety (Chinese STAI,
state), anxiety (Chinese
STAI, trait), general
mental health (Chinese
GHQ)
4 weeks Relaxation
B Administrative nursing
staff, Hong Kong,
China (T ⫽ 18, C
⫽ 30)
Relaxation using cognitive
imagery
Relaxation
(table continues)
81EFFECTS OF STRESS MANAGEMENT INTERVENTIONS

Many of the interventions had multiple components
(such as cognitive– behavioral skills training and
meditation). Fourteen of the studies evaluated inter-
ventions with four or more treatment components.
Table 1 provides a summary of the included studies.
Outcome Variables
Each study contained multiple outcome mea-
sures. We selected and coded all dependent vari-
ables that related to stress, including psychologi-
cal, physiological, and organizational outcomes.
This resulted in more than 60 different outcome
variables, or an average of 3– 4 outcomes per
study. We averaged these outcomes at the treat-
ment– control contrast level to calculate a com-
bined effect size for each intervention. Psycholog-
ical measures were used in 35 out of 36 studies.
The most common among these were stress (k ⫽
14), anxiety (k ⫽ 13), general mental health (k ⫽
11), and job/work satisfaction (k ⫽ 10). Unfortu-
nately, there was no uniform scale used for any
construct. For example, stress was measured via 11
different scales, including the Job Stress Index
(Sandman, 1992), Occupational Stress Inventory
(Osipow & Spokane, 1983), Perceived Stress Scale
(Cohen, Kamarck, & Mermelstein, 1983), Personal
and Organizational Quality Assessment (Barrios-
Choplin & Atkinson, 2000), and Teacher Stress
Measure (Pettegrew & Wolf, 1982).
Physiological measures were used in a quarter of
the studies, and the most common of these was sys-
tolic and diastolic blood pressure. Other physiologi-
cal measures were epinephrine and norepinephrine
levels, galvanic skin response, and cholesterol. Only
six studies measured organizational-specific out-
comes. Four studies assessed absenteeism, and two
examined productivity.
Effect Sizes
A combined analysis, using the inverse-variance
weighted average effect size from each individual
intervention, yielded a significant effect size across
all studies (d ⫽ 0.526, 95% CI ⫽ 0.364, 0.687). This
is considered a medium to large effect size (J. Cohen,
1988). By comparison, van der Klink et al.’s (2001)
meta-analysis yielded a small combined effect size
(d ⫽ 0.34, 95% CI ⫽ 0.27, 0.41). We checked for
heterogeneity of effects in two ways. First, we used
the traditional chi-square statistic to test the hypoth-
esis that all of the observed heterogeneity was due to
sampling error variance. The Q value was highly
Table 1
(continued)
Author(s) and year
Treatment-control
contrast
Sample size
a
and
description
b
Treatment components Outcomes measured
c
Length
Intervention
type
Zolnierczyk-Zreda (2002) A Financial sector office
workers, Poland (T
⫽ 40, C ⫽ 45)
Cognitive-behavioral skills,
job control, social
support, assertiveness,
anger control
Problem-focused coping,
emotional-focused
coping, social support
10 weeks Multimodal
Note. T ⫽ treatment; C ⫽ control; GHQ-12 ⫽ General Health Questionnaire 12; JIG ⫽ Job in General Scale; DSP ⫽ Derogatis Stress Profile; OSI ⫽ Occupational Stress
Inventory; DCL ⫽ DeVilliers Carson Leary Scale; MBI ⫽ Maslach Burnout Inventory; SISS ⫽ Stress in the School Setting; JSI ⫽ Job Stress Index; STAI ⫽ State Trait Anxiety
Inventory; SSI ⫽ Social Support Indicator; OSQ ⫽ Occupational Stress Questionnaire; PSS ⫽ Perceived Stress Scale; SCL-90 ⫽ Symptom Checklist 90; PSQ ⫽ Personal Strain
Questionnaire; RAS ⫽ Rathus Assertiveness Scale; STPI ⫽ State-Trait Personality Inventory; TQ4 ⫽ Teacher Questionnaire 4; BJSQ ⫽ Brief Job Stress Questionnaire; NSC ⫽
Nurse Stress Checklist; TOSQ ⫽ Teacher Occupational Stress Questionnaire; SRI ⫽ Stress Response Index; SMI ⫽ stress management intervention; SOS ⫽ Significant Others
Scale; RSES ⫽ Rosenberg Self-Esteem Scale.
a
Based on posttreatment measures.
b
U.S. sample, unless otherwise noted.
c
Frequently used scales noted in parentheses.
82 RICHARDSON AND ROTHSTEIN

significant (Q ⫽ 202.6, p ⬍ .001), indicating that
there was more heterogeneity of effects than could be
accounted for by sampling error. Second, we used the
I
2
statistic: I
2
⫽ [(Q – df)/Q] ⫻ 100%, where Q is the
chi-square statistic and df is its degree of freedom
(Higgins, Thompson, Deeks, & Altman, 2003). I
2
represents the amount of variability across studies
that is attributable to between-study differences
rather than to sampling error variability. In this case,
the I
2
statistic suggests that 73% of the total variance
is due to between-study variance, or heterogeneity,
rather than to sampling error. Both statistics sug-
gested the likely presence of moderators, so we pro-
ceeded to conduct subgroup analyses.
Intervention-Level Moderators
To search for moderators, we classified the inter-
ventions into more homogeneous subgroups and per-
formed analyses on these groupings, again using the
average outcome effect size for each intervention,
when more than one outcome was assessed. First, we
coded our interventions into the same categories used
in the van der Klink et al. (2001) meta-analysis:
cognitive– behavioral, relaxation, organizational, or
multimodal (multiple component). Seven interven-
tions could not be classified into these groupings.
These studies evaluated interventions composed of
exercise or EMG feedback, journaling, personal
skills development, or classroom management train-
ing (for teachers). We therefore created an “alterna-
tive” intervention category, while recognizing that
this grouping did not represent a specific type of
intervention. Table 2 shows the average effect size
for interventions in each of these categories.
The results in Table 2 show that the average effect
sizes of both the cognitive– behavioral and the relax-
ation intervention categories were larger than the
analogous average effects from the van der Klink et
al. (2001) meta-analysis. Somewhat surprisingly,
there was a great deal of heterogeneity of effects in
the cognitive– behavioral intervention category (I
2
⫽
89.5, Q ⫽ 57.0, p ⬍ .001). The alternative interven-
tion category had the second largest average effect
size (d ⫽ 0.909, 95% CI ⫽ 0.318, 1.499), although it
also had a wide confidence interval and, as would be
expected, substantial heterogeneity (I
2
⫽ 85.3, Q ⫽
40.8, p ⬍ .001). Organizational interventions yielded
virtually no effect, also consistent with the prior
meta-analysis. Multimodal interventions, however,
yielded a significant but small effect size in the
present study (d ⫽ .239, 95% CI ⫽ 0.092, 0.386),
which is lower than the van der Klink et al. study.
The present meta-analysis included 15 studies (19
interventions) with multimodal programs, whereas
the van der Klink et al. study included only 8 studies
in this category. Within such multimodal programs,
cognitive– behavioral, relaxation, and even organiza-
tional techniques can all be included as treatment
components. Among the 19 multimodal interventions
in our meta-analysis, 5 included cognitive– behav-
ioral components, 3 included relaxation components,
and 11 included both cognitive– behavioral and re-
laxation components. This makes it difficult to assess
whether the specific components, the mixture of com-
ponents, the number of components, or a combina-
tion of these factors is causing the intervention effect.
Another way to categorize our studies is to look at the
number of components per intervention. Table 3
shows the effect sizes based on these subgroups.
The results in Table 3 suggest that interventions
that focus on a single component are more effective
than those that focus on multiple components. The
general trend is that as each component is added, the
effect is reduced. However, there was significant
heterogeneity among the one-component studies
(I
2
⫽ 81.6, Q ⫽ 103.0, p ⬍ .001), and the results in
Table 3 are confounded by intervention type. For
Table 2
Cohen’s d and Confidence Intervals on the Basis of Intervention Type
Intervention type kN d 95% CI y
Cognitive-behavioral 7 448 1.164
**
0.456, 1.871 .68
*
Relaxation 17 705 0.497
***
0.309, 0.685 .35
*
Organizational 5 221 0.144 ⫺0.123, 0.411 .08
Multimodal 19 862 0.239
**
0.092, 0.386 .51
*
Alternative 7 455 0.909
**
0.318, 1.499 N/A
Note. k ⫽ number of interventions; d ⫽ combined effect size; CI ⫽ confidence interval; y ⫽
Cohen’s d from van der Klink et al. (2001).
*
p ⬍ .05.
**
p ⬍ .01.
***
p ⬍ .001.
83EFFECTS OF STRESS MANAGEMENT INTERVENTIONS

example, the one-component interventions with the
largest effects were cognitive– behavioral interven-
tions (k ⫽ 2, d ⫽ 1.230, 95% CI ⫽⫺0.968, 3.428).
Four of the single-component interventions taught
some form of personal development skills that spe-
cifically related to increasing personal resources or
management skills that would assist employees in
their jobs (e.g., classroom management training).
These yielded a significant large effect (d ⫽ 1.154,
95% CI ⫽ 0.332, 1.975). Seven used relaxation as the
treatment and obtained a significant medium effect
(d ⫽ 0.501, 95% CI ⫽ 0.161, 0.841).
Among the studies with two treatment compo-
nents, relaxation techniques were most likely to be
the primary treatment component. This was the case
with 10 interventions, yielding a significant medium
effect size (d ⫽ 0.502, 95% CI ⫽ 0.265, 0.739).
Seven interventions used cognitive– behavioral tech-
niques as the primary treatment component, and these
yielded a significant large effect size (d ⫽ 0.913,
95% CI ⫽ 0.320, 1.505). Among the studies with
four or more treatment components, cognitive–
behavioral skills training and relaxation were likely
to be incorporated. Nine interventions included both
cognitive– behavioral and relaxation components
(d ⫽ 0.296, 95% CI ⫽ 0.086, 0.507), three included
cognitive– behavioral components (d ⫽ 0.201, 95%
CI ⫽⫺0.119, 0.522), and three included relaxation
components (d ⫽ 0.215, 95% CI ⫽⫺0.069, 0.499).
We also examined whether treatment duration
made a difference among the interventions. The av-
erage length was 7.4 weeks, but the range was 3 days
to 7 months. We therefore grouped studies according
to the length of the intervention period (three studies
did not provide this information). Because treatment
length may be confounded with type of intervention,
we further classified the studies based on intervention
type. Table 4 shows the effect sizes based on these
subgroups. The “All studies” column suggests that
shorter interventions are more effective than longer
ones. However, when one examines the data by in-
tervention type, the pattern does not hold as firmly.
The majority of interventions fall under the relax-
ation and multimodal categories, but there are a lim-
ited number of studies in each cell. Relaxation inter-
ventions consistently produce medium-sized effects,
regardless of length. Multimodal programs, in con-
trast, appear to lose effect as treatment length in-
creases.
Outcome-Level Moderators
Another way to classify the data into subgroups is
to examine the outcome measures used in the studies.
Outcome measures could be psychological, physio-
logical, or organizational in nature, and we coded
them into 40 general categories. Some measures were
used more frequently than others. To assess which
measures produced larger effects and to examine
whether outcome variables differed between inter-
vention types, we performed a subgroup analysis of
intervention type crossed with the outcomes we noted
were used most frequently. Table 5 shows the effect
sizes based on these subgroups.
Disaggregating the data by outcome variable and
treatment type results in a small number of interven-
tions in certain cells, but the analysis does illustrate
several interesting findings. First, no studies that
evaluated single-mode cognitive– behavioral or orga-
nizational interventions measured physiological out-
comes. Thus, the large effect of the single-mode
cognitive– behavioral programs is based solely on
psychological and (less frequently) organizational
measures. Likewise, the large effects of alternative
interventions are also based primarily on psycholog-
ical variables. A pattern thus emerges in which out-
Table 3
Cohen’s d and Confidence Intervals on the Basis of the Number of
Treatment Components
No. of
treatment
components kN d 95% CI
One 20 946 0.643
***
0.309, 0.977
Two 18 970 0.607
***
0.346, 0.868
Three 2 59 ⫺0.104 ⫺0.627, 0.418
Four or more 15 716 0.271
**
0.102, 0.440
Note. k ⫽ number of interventions; d ⫽ combined effect size; CI ⫽ confidence interval.
**
p ⬍ .01.
***
p ⬍ .001.
84 RICHARDSON AND ROTHSTEIN

come variables are likely to be chosen on the basis of
the type of intervention. For example, interventions
that focus on the individual (e.g., cognitive–
behavioral, journaling, and stress education) use psy-
chological measures, and those that focus on organi-
zational changes generally include organizational
measures. The result is that we are left with gaps in
the body of research. We are unable to assess whether
alternative treatment programs (e.g., journaling, ex-
ercise, and personal coping skills)—which have a
large effect on psychological and physiological out-
comes—produce similar results using organizational
measures. Regarding specific organizational out-
comes, measures of productivity appear to produce
larger effects than absenteeism, but there is a general
lack of studies that use such measures. In general,
there are no uniform outcome measures used to as-
sess the effectiveness of stress management pro-
grams. Only one third of the interventions reported
using an actual measure of “stress,” and among these
there was significant variation in the scales chosen.
To obtain a more pure assessment of whether type
of outcome measure played a moderating role, we
selected only those studies for which psychological
outcomes were provided in combination with either
physiological or organizational measures. In other
words, the same samples of participants were being
measured using both types of outcomes. All of the
psychological measures were based on self-report,
continuous scales. This may affect the reliability of
the outcomes. The physiological measures, in con-
trast, were more likely to be administered by an
Table 4
Cohen’s d on the Basis of Length of Treatment and Intervention Type
Length of
treatment All studies
Treatment type
CB Relax Org Multi Alternative
1–4 weeks 0.804
***
(15)
1.477
**
(2)
0.560
*
(5)
⫺0.097 (1) 0.274 (3) 1.217
*
(4)
5–8 weeks 0.396
***
(22)
1.576 (2) 0.500
***
(7)
⫺0.003 (2) 0.291
*
(9)
0.585
*
(2)
9–12 weeks 0.346
*
(10)
1.230 (2) 0.315 (3) N/A 0.089 (4) 0.250 (1)
⬎12 weeks 0.401
**
(4)
0.323 (1) N/A 0.328 (2) 0.718
*
(1)
N/A
Note. Numbers in parentheses represent total number of interventions. CB ⫽ cognitive-behavioral; Relax ⫽ relaxation;
Org ⫽ organizational; Multi ⫽ multimodal.
*
p ⬍ .05.
**
p ⬍ .01.
***
p ⬍ .001.
Table 5
Cohen’s d on the Basis of Outcome Variables and Intervention Type
Outcome variable All studies
Treatment type
CB Relax Org Multi Alternative
Psychological
All combined 0.535
***
(52)
1.154
**
(7)
0.507
***
(16)
0.134 (5) 0.258
**
(18)
0.905
**
(6)
Stress 0.727
***
(18)
1.007
**
(5)
0.834
**
(5)
⫺0.314 (2) 0.595
**
(5)
1.367
***
(1)
Anxiety 0.678
***
(22)
2.390
***
(1)
0.611
***
(5)
N/A 0.418
**
(12)
0.841 (4)
Mental health 0.441
***
(16)
0.708
*
(1)
0.405
*
(5)
0.167 (3) 0.518 (5) 0.616
*
(2)
Work-related outcomes
a
0.183 (23) 0.682 (4) ⫺0.381 (4) 0.243 (4) ⫺0.115 (7) 0.794 (4)
Physiological
All combined 0.292
*
(14)
N/A 0.312 (5) N/A 0.166 (7) 0.714
**
(2)
Organizational
All combined 0.267 (11) 0.606 (1) 0.534
***
(4)
0.247 (3) ⫺0.122 (3) N/A
Productivity 0.703
***
(4)
0.606 (1) 0.661
***
(2)
0.989
**
(1)
N/A N/A
Absenteeism ⫺0.059 (7) N/A 0.213 (2) ⫺0.159 (2) ⫺0.122 (3) N/A
Note. Numbers in parentheses represent total number of interventions. CB ⫽ cognitive-behavioral; Relax ⫽ relaxation;
Org ⫽ organizational; Multi ⫽ multimodal.
a
Includes job/work satisfaction, motivation, social support, daily hassles, role ambiguity, role overload, and perceived
control.
*
p ⬍ .05.
**
p ⬍ .01.
***
p ⬍ .001.
85EFFECTS OF STRESS MANAGEMENT INTERVENTIONS

independent, trained examiner or via a medical de-
vice (e.g., blood pressure monitor). The organiza-
tional measures were based on company records
(e.g., absenteeism) and self-report data (e.g., produc-
tivity or propensity to innovate). Table 6 shows the
effect sizes based on these subgroups.
The data in Table 6 are based on a small number of
studies and should therefore be interpreted cau-
tiously. Even so, it appears that intervention type
continues to confound outcome effects. The results
for all studies combined suggest that psychological
and physiological outcome variables produce compa-
rable effect sizes. However, this depends on type of
intervention. For example, for the alternative sub-
group, the physiological measures produced larger
effect sizes. When studies measured both psycholog-
ical and organizational variables, psychological out-
comes produced larger effects than organizational
outcomes. But this may also depend on treatment
type, as the relationship is reversed for the relaxation
and organizational subgroups. Table 6 does alert us to
the overreliance on self-report measures in interven-
tion studies. Among the 55 interventions, only 11
measured both psychological and physiological out-
comes, and 11 measured both psychological and or-
ganizational outcomes.
Sample-Level Moderators
The final moderator analysis we performed was
based on industry sector. Many early intervention
studies were performed in the health care or educa-
tion fields. We classified studies into subgroups on
the basis of three industry sectors: office, health care,
and education. We further grouped the results by
intervention type. Table 7 shows the effect sizes
based on these subgroups. Results depict effect sizes
in the general direction of prior analyses, with cog-
nitive– behavioral producing the largest effects.
However, what may be more interesting is to exam-
ine the distribution of intervention type by industry.
For example, multimodal interventions appear more
likely to be used in office settings, perhaps because
there has been no solid empirical evidence as to the
most effective treatment in this particular setting, and
therefore a “potpourri” approach is used. In contrast,
relaxation interventions appear more often within
health care settings, and cognitive– behavioral inter-
ventions in education settings. However, disaggregat-
ing the data produces small numbers of studies in
each cell, so these interpretations may be unstable.
Outlier Analysis
We performed outlier analyses by examining for-
est plots of the effect sizes and confidence intervals,
for all studies combined and at the subgroup levels.
One alternative intervention was identified as a pos-
sible outlier because of its very large effect size and
the fact that its confidence interval did not fall into
the range of similar interventions for that subgroup.
We therefore excluded this study (which represented
two alternative interventions: exercise only and lis-
tening to music; Taylor, 1991) from the analysis.
However, based on a sensitivity analysis, we note
that if we included this study in our calculations, the
combined overall effect size would increase slightly
(d ⫽ 0.618, 95% CI ⫽ 0.432, 0.903).
Table 6
Cohen’s d on the Basis of Outcome Variable and Intervention Type for Selected Studies
Outcome variable All studies
Treatment type
CB Relax Org Multi Alternative
Psychological vs.
physiological
Psychological 0.227
*
(11)
N/A 0.303
*
(4)
N/A 0.151 (6) 0.250 (1)
Physiological 0.219 (11) N/A 0.282 (4) N/A 0.115 (6) 0.601 (1)
Psychological vs.
organizational
Psychological 0.285
**
(11)
0.253 (1) 0.376
*
(4)
0.187 (3) 0.197 (3) N/A
Organizational 0.267 (11) 0.606 (1) 0.534
***
(4)
0.247 (3) ⫺0.122 (3) N/A
Note. Numbers in parentheses represent total number of interventions. CB ⫽ cognitive-behavioral; Relax ⫽ relaxation;
Org ⫽ organizational; Multi ⫽ multimodal.
*
p ⬍ .05.
**
p ⬍ .01.
***
p ⬍ .001.
86 RICHARDSON AND ROTHSTEIN

Sensitivity Analysis
We performed a sensitivity analysis to examine
whether including seven additional studies from the
van der Klink et al. (2001) meta-analysis would
change our overall results. These particular studies
did not meet our inclusion criteria because, according
to our review, they did not report sufficient statistics
to calculate an effect size.
1
They were included in the
van der Klink et al. study on the basis of assumptions
made by those authors. However, rather than exclude
these interventions entirely, we used the reported
effect sizes from the van der Klink et al. study and
added them to our meta-analysis. This slightly re-
duced our combined overall effect size (d ⫽ 0.469,
95% CI ⫽ 0.328, 0.609) but still yielded a medium
effect.
Publication Bias
We performed an analysis to examine whether the
combined effect size from published studies differed
from that of unpublished studies. The current meta-
analysis included five unpublished dissertations, rep-
resenting eight interventions. The combined effect
size from these eight interventions, using the average
effect size across outcomes, yielded a significant
medium to large effect (d ⫽ 0.553, 95% CI ⫽
⫺0.126, 1.232, p ⫽ .110). In comparison, the com-
bined effect from published studies was .509 (95%
CI ⫽ 0.356, 0.661, p ⬍ .001). In this case, it appears
that including unpublished studies slightly increased
the size of our overall average effect, whereas the
general concern is that omission of unpublished work
upwardly biases the effect size. We have no unam-
biguous explanation for the direction of difference in
our particular case. There were no apparent differ-
ences in methodological quality between the two
groups of studies.
Another way to detect publication bias in a meta-
analysis is the “trim-and-fill” technique, developed
by Duval and Tweedie (2000). “Trim and fill” is a
nonparametric method designed to estimate and ad-
just a funnel plot for the number and outcomes of
missing studies (Duval, 2005). We used this method
on the overall effect size distributions and estimated
the number of missing studies at six, all to the right
of the mean. This suggests that the combined effect
of 0.526 is understated and that the potential impact
of including the proposed “missing” studies would
increase the effect to 0.595. However, one limitation
of the trim-and-fill method is that if the data are
heterogeneous, the technique may impute studies that
are not really “missing.” Study-related factors may
distort the appearance of the funnel plot (Duval,
2005). To adjust for heterogeneity, we performed
additional trim-and-fill analyses at the subgroup
level, examining intervention type crossed with out-
come. We were able to use the method only if there
was a minimum of three interventions in the sub-
group. On the basis of the analyses, multimodal in-
terventions was the only category that produced
greater than one “missing” study. On the basis of the
psychological outcome measures, it appeared that
three studies were missing on the left side of the
mean, which would suggest an overstated effect and
would decrease the overall effect for multimodal
interventions (d ⫽ 0.190). We stress that the main
goal of the trim-and-fill method is as a sensitivity
1
For example, one study contained three distinct treat
-
ment modules but combined the participants of each into
one group and compared it with the control. Two studies
reported results of only the statistically significant findings,
and several others failed to report all required statistics (e.g.,
means with no standard deviations). In such cases, van der
Klink et al. (2001) used p values, making assumptions when
no such value was reported (e.g., nonsignificant findings).
Table 7
Cohen’s d Based on Industry Sector and Intervention Type
Industry All studies
Treatment type
CB Relax Org Multi Alternative
Office 0.680
***
(19)
0.872 (3) 0.619
***
(7)
0.162 (1) 0.395
*
(6)
1.337
**
(2)
Health care 0.492
***
(8)
0.988
***
(1)
0.462
***
(4)
0.208 (2) 1.307
*
(1)
N/A
Education 1.255
**
(7)
1.662
*
(3)
1.523
*
(1)
0.056 (1) 0.524 (1) 2.037
***
(1)
Note. Numbers in parentheses represent total number of interventions. CB ⫽ cognitive-behavioral; Relax ⫽ relaxation;
Org ⫽ organizational; Multi ⫽ multimodal.
*
p ⬍ .05.
**
p ⬍ .01.
***
p ⬍ .001.
87EFFECTS OF STRESS MANAGEMENT INTERVENTIONS

analysis to assess the impact of missing studies on the
overall effect, rather than actually adjusting the end
results (Duval, 2005).
Discussion
In the present study, we used meta-analysis proce-
dures to evaluate the effects of SMIs in workplace
settings. We updated a previous systematic review
performed by van der Klink et al. (2001). Thirty-
eight articles met our inclusion criteria, representing
36 studies and 55 interventions. A combined analy-
sis, using the weighted average effect size from each
individual intervention, yielded a significant effect
size (d ⫽ 0.526, 95% CI ⫽ 0.364, 0.687). However,
this overall analysis may be misleading as there is
significant heterogeneity within the studies. Further
analysis was required to determine what moderators
were present.
We classified interventions into more homoge-
neous subgroups and performed analyses on these
groupings to identify moderators. First, to be consis-
tent with the van der Klink et al. (2001) study, we
coded interventions on the basis of their treatment
components and categorized them into five sub-
groups: cognitive– behavioral, relaxation, organiza-
tional, multimodal, and alternative interventions. Al-
though we found larger effects in each of the four
subgroups that we had in common with van der Klink
et al., the relative effectiveness of the four groups
was the same in both meta-analyses, and van der
Klink et al.’s average effect size value for each cat-
egory was well within the 95% confidence intervals
around our mean effects. Thus, our research both
supports the results of the van der Klink et al. meta-
analysis and extends it by ruling out the threat that
weak study design in some of the included studies
was responsible for the observed effects. In fact, we
show that higher average effects were obtained when
only true experiments were included.
In the current meta-analysis, cognitive– behavioral
interventions (d ⫽ 1.164) and alternative interven-
tions (d ⫽ 0.909) yielded the largest effect sizes. On
the basis of the I
2
statistic and Q values, however,
there was substantial heterogeneity within each of
these subgroups. We therefore performed additional
subgroup analyses, and cognitive– behavioral inter-
ventions consistently produced larger effects than
other types of interventions. Our findings are in ac-
cord with other research that has shown cognitive–
behavioral interventions to be among the more effec-
tive methods for managing stress in other settings and
with other populations, including HIV-positive gay
men (Lutgendorf et al., 1998), women with early
stage breast cancer (Antoni et al., 1991), and students
(Stein et al., 2003). Similarly, cognitive therapy has
proved to be an effective treatment for a variety of
psychological, psychosomatic, and somatic disor-
ders, including depression and anxiety (Lipsey &
Wilson, 1993), chronic pain (Morley, Eccleston, &
Williams, 1999), chronic fatigue syndrome (Whiting
et al., 2001), and insomnia (Rybarczyk et al., 2005).
In an attempt to understand why cognitive–
behavioral interventions might produce stronger ef-
fects than other popular techniques such as relaxation
or meditation, we compared the goals of the methods.
Relaxation and meditation aim to refocus attention
away from the source of stress, to increase the per-
son’s awareness of the tension in his or her body and
mind, and to reduce this tension by “letting go.”
Although they may reduce or eliminate troubling
thoughts or feelings, they do not direct the individual
to confront dysfunctional ideas, emotions, or behav-
iors. Thus, these are basically passive techniques.
Cognitive– behavioral interventions, on the other
hand, are more active. These interventions encourage
individuals to take charge of their negative thoughts,
feelings, and resulting behavior by changing their
cognitions and emotions to more adaptive ones and
by identifying and practicing more functional behav-
ioral responses. In other words, cognitive–behavioral
interventions promote the development of proactive
as well as reactive responses to stress. This may
account for the relative magnitude of the two types of
treatments, but other differences, such as variations
in the length of the intervention and the mode of
instruction, will need to be ruled out by future re-
search.
Despite the stronger effects of cognitive– behav-
ioral interventions, the most popular treatment com-
ponents among the 55 interventions were relaxation
and meditation techniques. They were used in 69% of
the studies. On the basis of the subgroup analyses,
these programs consistently produced medium ef-
fects. A likely reason for the popularity of this treat-
ment is its simplicity. A survey of subject matter
experts rated relaxation as the most practical inter-
vention, because it is the least expensive and easiest
to implement (Bellarosa & Chen, 1997). Often these
techniques are self-taught via audiotapes. Cognitive–
behavioral interventions, in contrast, are generally
taught by a trained professional in a group session,
and therefore require a greater investment of organi-
zational resources.
A somewhat surprising finding from the current
study is that the more components added to a cogni-
88 RICHARDSON AND ROTHSTEIN

tive– behavioral intervention, the less effective it be-
comes. Single-mode cognitive– behavioral interven-
tions yielded a d of 1.230, but cognitive– behavioral
interventions with four or more components (e.g.,
including relaxation, assertiveness, time manage-
ment, etc.) yielded a d of 0.233. This finding contra-
dicts Murphy’s (1996) narrative review, in which he
concluded that “the most positive results were ob-
tained with a combination of two or more tech-
niques” (p. 112). Multimodal interventions are quite
common and are more likely to be of a longer dura-
tion. However, longer treatment programs were gen-
erally not associated with larger effect sizes. Organi-
zational researchers may be tempted to institute a
combination of treatments in hopes of producing
more effective stress management. We suggest that
when single components are resource intensive and
relatively multifaceted at the outset, as is the case
with cognitive–behavioral skills training, the organi-
zation’s ability to implement additional components
effectively may decrease and work to the detriment
of the more complex individual components. Simpler
interventions may not suffer from being bundled with
other components. For example, the effect of relax-
ation training varied less dramatically whether it was
delivered on its own (d ⫽ 0.497) or as part of a
package four or more components (d ⫽ 0.246). On
the basis of our meta-analysis, we suggest that cog-
nitive– behavioral programs should not generally be
combined with other treatments, but relaxation and
meditation can be used as part of a larger set of
treatment components. As one anonymous reviewer
noted, however, shorter programs—which are likely
to be more cost-effective and practical to imple-
ment—appear to be sufficient and perhaps even bet-
ter than programs of longer duration.
The alternative interventions yielded a large aver-
age effect, and several of these are worth noting.
Three studies (Chen, 2006; Sharp & Forman, 1985;
Thomason & Pond, 1995) incorporated an interven-
tion designed to increase employees’ personal re-
sources or management/job skills, and they produced
a combined significant large effect (d ⫽ 1.414, CI ⫽
0.587, 2.241). We made the decision to code these
interventions as alternative rather than organizational
because they were designed to provide employees
with individual tools to assist them with the more
stressful aspects of their work rather than to make
structural changes in their jobs. For example, Chen
(2006) designed an intervention to increase partici-
pants’ personal resources during the introduction of a
new information technology system, and Sharp and
Forman (1985) provided classroom management
training to teachers. As these interventions may be
thought to address organizational issues, we con-
ducted a reanalysis by putting them in the organiza-
tional subgroup. This increased the average effect of
organizational interventions from 0.144 (k ⫽ 5, CI ⫽
⫺0.123, 0.411) to 0.595 (k ⫽ 8, CI ⫽⫺0.044,
1.233). This sensitivity analysis both illustrates that
the small number of studies in particular categories
affects the stability of the results for that subgroup
and provides evidence that programs that increase the
employee’s job-related skills and abilities may be an
effective way to reduce employee stress. We suggest
that new primary studies are needed for this category
of intervention.
Our examination of outcome measures by inter-
vention type revealed several other gaps in the liter-
ature. As noted in earlier reviews (Murphy & Sauter,
2003; van der Klink et al., 2001), there remains a lack
of studies that assess organizational-level outcomes.
We suggest that future primary studies attend to this
level of outcome. We further suggest that we will
learn more about the mechanisms by which interven-
tions reduce stress and be able to more meaningfully
compare interventions by incorporating each of the
three types of outcome measures in each evaluation.
Currently, researchers tend to choose outcome mea-
sures that are highly aligned with the intervention.
Thus, exercise interventions will almost always use
physiological measures, cognitive– behavioral and
relaxation programs will use psychological measures,
and organizational interventions will include at least
one organizational outcome. Matching intervention
to outcome type makes sense but also creates con-
founds between intervention and type of outcome.
For example, in our sample of studies, no single-
mode cognitive– behavioral intervention used physi-
ological outcome measures. These interventions
achieved some of the largest effects on the basis of
psychological variables, but how would they have
compared with exercise interventions if they had
measured cardiovascular functioning? New primary
research comparing different interventions on similar
outcomes would contribute to both theoretical and
applied literatures on worksite stress management.
Limitations
A limitation of this meta-analysis is that there is
limited information to assess the effects of organiza-
tional-level interventions or organizational-level out-
comes. The majority of studies reported only psycho-
logical-level outcome measures, and there were very
few studies with organizational-level outcomes (e.g.,
89EFFECTS OF STRESS MANAGEMENT INTERVENTIONS

absenteeism and performance). Of the 36 studies,
only 5 assessed the impact of an organizational in-
tervention. One reason for this is because of the strict
inclusion criteria we applied to our literature search.
We limited the type of studies to only those experi-
ments with random assignment to treatment and con-
trol groups, and it is likely to be difficult to conduct
true experiments on organizational interventions. On
the other hand, this may reflect the true state of the
research literature, as reviews with less stringent in-
clusion criteria also lament the lack of evaluation
of organizational interventions (Giga, Noblet,
Faragher, & Cooper, 2003; Murphy & Sauter, 2003).
Another limitation of this meta-analysis is that the
moderators we examined are confounded by the type of
participants in each study, and with each other. Our
overall effect size is an average of several heteroge-
neous effects, which may have been produced by dif-
ferences in the characteristics of the sample participants
as well as in the intervention type. The wide variety of
intervention types and outcome variables makes for a
multitude of effect combinations. We have attempted to
classify the interventions into the most meaningful sub-
groups while keeping in mind that subgrouping leads to
decreased power and precision.
A final limitation is that we cannot account for the
varying organizational stress levels before the inter-
vention and how they may have influenced the size
and variability of treatment effects. Some studies in
our sample did prescreen employees and selected
participants who, although not clinically diagnosed
with a stress-related illness, scored moderate to high
on initial stress screenings. Other studies simply re-
cruited employees through public notice. We cannot
make the assumption that pretreatment stress levels
among our sample studies were uniformly high sim-
ply because the organizations were willing to partic-
ipate in an intervention. An anonymous reviewer
noted that often the organizations with the most
stressful environments are the ones whose manage-
ment does not see the value in investing in training.
Future Research
The overall significant medium to large effect size
indicates that there is value to SMI programs. These
results show that individual employees can be taught
techniques to reduce their stress levels and alleviate
symptoms of strain. In addition, nearly all of the
subcategories of interventions produced meaningful
effects. Some of these, such as cognitive–behavioral
interventions and meditation, have been the focus of
a relatively large number of studies, but not all of the
potentially effective treatments have been studied very
often. Specifically, single-mode treatment programs
that provide employees with personal job-related skills
and abilities (e.g., resource enhancement and goal set-
ting) need more attention by researchers.
Our moderator analyses, even for popular interven-
tions, are based on small numbers of studies. Further-
more, it was not possible to remove potential con-
founds such as the one between type of intervention
and outcome type. Thus, future research that system-
atically disentangles the confounding in the current
body of literature would contribute to our knowledge
of the effectiveness of different types of programs.
Little is known about the long-term effects of
SMIs. In all of the studies in this meta-analysis, the
posttreatment measures were taken either immedi-
ately after training or within several weeks. Only a
quarter of the interventions (k ⫽ 15) included fol-
low-up measures subsequent to the posttreatment
evaluation. It would be useful to know how long
these effects last. Recent research on time away from
work (i.e., respites) has found empirical evidence to
suggest a direct relationship between occupational
stress and strain. Studies have found that time away
from work will alleviate stress symptoms, but no
matter how long the respite—whether a weekend or
year-long sabbatical—employees ultimately return to
prerespite stress levels (Eden, 2001). We need addi-
tional primary studies to assess whether a similar
pattern develops with SMIs.
Finally, the present meta-analysis illustrates that
after 30 years of work, there are a large number of
methodologically rigorous intervention studies in the
stress management literature. We hope the results
encourage future researchers to strive to design qual-
ity experiments that incorporate random assignment
to treatment and control groups and report the results
of all outcomes, not just the statistically significant
ones. In addition, we promote the continued use of
meta-analytic procedures to synthesize the research.
As more primary studies are conducted, it is impor-
tant to update systematic reviews and continue to
reassess the results.
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Received June 1, 2006
Revision received February 17, 2007
Accepted March 18, 2007
y
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